def cluster_newsitems(qs, radius=26):
"""
A convenience function for clustering a newsitem queryset.
"""
return clustering.cluster_scales(
dict([(ni.id, (ni.location.centroid.x, ni.location.centroid.y))
for ni in qs if ni.location]),
radius)
def timeit(label, f, *args, **kwargs):
import time, sys
start = time.time()
ret_val = f(*args, **kwargs)
print >> sys.stderr, "%s took %.4f seconds" % (label, time.time() - start)
return ret_val
def randomize(L):
import copy, random
Lprime = copy.copy(L)
random.shuffle(Lprime)
return Lprime
def main():
buffer = 20
objs = gen_test_objs(rand_seed="foo")
bunches = timeit("cluster", cluster.buffer_cluster, objs, buffer)
display(bunches, buffer=buffer, f=print_bunches)
if __name__ == "__main__":
#main()
#for bunch in cluster_by_scale(sample.sample_pts, 51, 19200):
#print "%3d: (%.4f, %.4f)" % (len(bunch.objects), bunch.x, bunch.y)
from django.utils.simplejson import dumps
print dumps(cluster_scales(sample.sample_pts, 26), cls=json.ClusterJSON)
pylab.show()
def display(bunches, buffer, f=plot_bunches):
f(bunches, buffer)
def timeit(label, f, *args, **kwargs):
import time, sys
start = time.time()
ret_val = f(*args, **kwargs)
print >> sys.stderr, "%s took %.4f seconds" % (label, time.time()-start)
return ret_val
def randomize(L):
import copy, random
Lprime = copy.copy(L)
random.shuffle(Lprime)
return Lprime
def main():
buffer = 20
objs = gen_test_objs(rand_seed="foo")
bunches = timeit("cluster", cluster.buffer_cluster, objs, buffer)
display(bunches, buffer=buffer, f=print_bunches)
if __name__ == "__main__":
#main()
#for bunch in cluster_by_scale(sample.sample_pts, 51, 19200):
#print "%3d: (%.4f, %.4f)" % (len(bunch.objects), bunch.x, bunch.y)
from django.utils.simplejson import dumps
print dumps(cluster_scales(sample.sample_pts, 26), cls=json.ClusterJSON)